Model translation method and device and computer readable storage medium

Abstract

The invention provides a model translation method and device and a computer readable storage medium. The method comprises the steps of obtaining a to-be-translated model and a training data set; converting the neural network layer of the to-be-translated model into a target neural network layer supported by a target processor to obtain a target model; and training the target model according to the training data set to determine parameters of each target neural network layer in the target model. By means of the method, the model generated under the specific framework can be converted into the target model capable of being operated by the target processor, and therefore the implementation scene of the model is expanded.

Description

technical field

[0001] The present application belongs to the field of artificial intelligence, and in particular relates to a model translation method, device and computer-readable storage medium. Background technique

[0002] This section is intended to provide a background or context to the implementations of the application that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section.

[0003] Engineers usually use frameworks such as TensorFlow to create neural network models, and some use Caffe frameworks or Darknet frameworks to create neural network models.

[0004] However, in the prior art, neural network models created under different frameworks can only run on specific processors. In other words, models trained based on these commonly used frameworks may not be able to run directly on other general-purpose processors, that is, There is a format incompatibility between the model and the processor. Therefor...

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